Overview

Dataset statistics

Number of variables29
Number of observations51
Missing cells57
Missing cells (%)3.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory234.5 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-12" Constant
_embedded_show_dvdCountry has constant value "nan" Constant
url has a high cardinality: 51 distinct values High cardinality
_links_self_href has a high cardinality: 51 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
season is highly correlated with runtime and 2 other fieldsHigh correlation
runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with season and 2 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_summary and 12 other fieldsHigh correlation
summary is highly correlated with url and 5 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 12 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
_embedded_show_status is highly correlated with url and 6 other fieldsHigh correlation
url is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
image is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_summary and 7 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
name is highly correlated with url and 5 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_links_self_href is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
type is highly correlated with summary and 5 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_language is highly correlated with url and 5 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 18 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
id is highly correlated with url and 19 other fieldsHigh correlation
url is highly correlated with id and 25 other fieldsHigh correlation
name is highly correlated with id and 24 other fieldsHigh correlation
season is highly correlated with url and 14 other fieldsHigh correlation
number is highly correlated with id and 13 other fieldsHigh correlation
type is highly correlated with url and 5 other fieldsHigh correlation
airtime is highly correlated with id and 17 other fieldsHigh correlation
airstamp is highly correlated with id and 21 other fieldsHigh correlation
runtime is highly correlated with id and 19 other fieldsHigh correlation
image is highly correlated with id and 24 other fieldsHigh correlation
summary is highly correlated with url and 19 other fieldsHigh correlation
_embedded_show_id is highly correlated with url and 14 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_type is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_status is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with id and 18 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with id and 18 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_ended is highly correlated with url and 12 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_weight is highly correlated with url and 15 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 24 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 19 other fieldsHigh correlation
_links_self_href is highly correlated with id and 25 other fieldsHigh correlation
number has 1 (2.0%) missing values Missing
runtime has 5 (9.8%) missing values Missing
image has 32 (62.7%) missing values Missing
_embedded_show_runtime has 14 (27.5%) missing values Missing
_embedded_show_averageRuntime has 5 (9.8%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_embedded_show_url is uniformly distributed Uniform
_embedded_show_name is uniformly distributed Uniform
_embedded_show_officialSite is uniformly distributed Uniform
_embedded_show_summary is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique
_embedded_show_weight has 1 (2.0%) zeros Zeros

Reproduction

Analysis started2022-05-10 02:09:04.183379
Analysis finished2022-05-10 02:09:46.396599
Duration42.21 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2039962.608
Minimum1943280
Maximum2318102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:46.603550image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1943280
5-th percentile1961672
Q11980152.5
median1986253
Q32057147
95-th percentile2250743.5
Maximum2318102
Range374822
Interquartile range (IQR)76994.5

Descriptive statistics

Standard deviation97359.48045
Coefficient of variation (CV)0.04772611031
Kurtosis1.466474142
Mean2039962.608
Median Absolute Deviation (MAD)14313
Skewness1.540898638
Sum104038093
Variance9478868433
MonotonicityNot monotonic
2022-05-09T21:09:46.923839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19888591
 
2.0%
23112131
 
2.0%
19861571
 
2.0%
19861581
 
2.0%
20000581
 
2.0%
20000591
 
2.0%
20399361
 
2.0%
21102461
 
2.0%
21817961
 
2.0%
22893211
 
2.0%
Other values (41)41
80.4%
ValueCountFrequency (%)
19432801
2.0%
19537881
2.0%
19612871
2.0%
19620571
2.0%
19670681
2.0%
19719391
2.0%
19719401
2.0%
19723461
2.0%
19725651
2.0%
19725661
2.0%
ValueCountFrequency (%)
23181021
2.0%
23112131
2.0%
22893211
2.0%
22121661
2.0%
21868681
2.0%
21821171
2.0%
21817961
2.0%
21761291
2.0%
21389251
2.0%
21376021
2.0%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21
 
1
https://www.tvmaze.com/episodes/2311213/ano-ko-no-yume-wo-mitan-desu-1x11-the-dark-eaters
 
1
https://www.tvmaze.com/episodes/1986157/the-burning-river-1x07-episode-7
 
1
https://www.tvmaze.com/episodes/1986158/the-burning-river-1x08-episode-8
 
1
https://www.tvmaze.com/episodes/2000058/ultimate-note-1x11-episode-11
 
1
Other values (46)
46 

Length

Max length122
Median length94
Mean length81.39215686
Min length58

Characters and Unicode

Total characters4151
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21
2nd rowhttps://www.tvmaze.com/episodes/1986140/soul-land-7x04-di134ji
3rd rowhttps://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mind
4th rowhttps://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-country
5th rowhttps://www.tvmaze.com/episodes/1972565/the-wolf-1x23-episode-23

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-211
 
2.0%
https://www.tvmaze.com/episodes/2311213/ano-ko-no-yume-wo-mitan-desu-1x11-the-dark-eaters1
 
2.0%
https://www.tvmaze.com/episodes/1986157/the-burning-river-1x07-episode-71
 
2.0%
https://www.tvmaze.com/episodes/1986158/the-burning-river-1x08-episode-81
 
2.0%
https://www.tvmaze.com/episodes/2000058/ultimate-note-1x11-episode-111
 
2.0%
https://www.tvmaze.com/episodes/2000059/ultimate-note-1x12-episode-121
 
2.0%
https://www.tvmaze.com/episodes/2039936/tregayes-way-in-the-kitchen-1x05-taco-night-any-night1
 
2.0%
https://www.tvmaze.com/episodes/2110246/paranormal-nightmare-5x06-a-haunting-in-west-virginia1
 
2.0%
https://www.tvmaze.com/episodes/2181796/i-like-to-watch-3x08-selena-the-series1
 
2.0%
https://www.tvmaze.com/episodes/2289321/blippi-2020-12-12-blippi-goes-indoor-skydiving-fun-and-educational-videos-for-kids1
 
2.0%
Other values (41)41
80.4%

Length

2022-05-09T21:09:47.351387image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-211
 
2.0%
https://www.tvmaze.com/episodes/1971939/hver-gang-vi-motes-10x13-program-7-del-11
 
2.0%
https://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mind1
 
2.0%
https://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-country1
 
2.0%
https://www.tvmaze.com/episodes/1972565/the-wolf-1x23-episode-231
 
2.0%
https://www.tvmaze.com/episodes/1972566/the-wolf-1x24-episode-241
 
2.0%
https://www.tvmaze.com/episodes/1998578/mr-right-is-here-1x07-episode-71
 
2.0%
https://www.tvmaze.com/episodes/1998579/mr-right-is-here-1x08-episode-81
 
2.0%
https://www.tvmaze.com/episodes/2113320/klassen-3x18-herman-dahl-tar-over1
 
2.0%
https://www.tvmaze.com/episodes/1977320/stjernestov-1x12-episode-121
 
2.0%
Other values (41)41
80.4%

Most occurring characters

ValueCountFrequency (%)
-340
 
8.2%
e340
 
8.2%
/255
 
6.1%
s247
 
6.0%
t247
 
6.0%
o224
 
5.4%
w186
 
4.5%
i169
 
4.1%
m148
 
3.6%
a148
 
3.6%
Other values (30)1847
44.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2779
66.9%
Decimal Number624
 
15.0%
Other Punctuation408
 
9.8%
Dash Punctuation340
 
8.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e340
12.2%
s247
 
8.9%
t247
 
8.9%
o224
 
8.1%
w186
 
6.7%
i169
 
6.1%
m148
 
5.3%
a148
 
5.3%
p144
 
5.2%
d112
 
4.0%
Other values (16)814
29.3%
Decimal Number
ValueCountFrequency (%)
1147
23.6%
2108
17.3%
084
13.5%
956
 
9.0%
850
 
8.0%
642
 
6.7%
740
 
6.4%
533
 
5.3%
333
 
5.3%
431
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/255
62.5%
.102
 
25.0%
:51
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-340
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2779
66.9%
Common1372
33.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e340
12.2%
s247
 
8.9%
t247
 
8.9%
o224
 
8.1%
w186
 
6.7%
i169
 
6.1%
m148
 
5.3%
a148
 
5.3%
p144
 
5.2%
d112
 
4.0%
Other values (16)814
29.3%
Common
ValueCountFrequency (%)
-340
24.8%
/255
18.6%
1147
10.7%
2108
 
7.9%
.102
 
7.4%
084
 
6.1%
956
 
4.1%
:51
 
3.7%
850
 
3.6%
642
 
3.1%
Other values (4)137
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-340
 
8.2%
e340
 
8.2%
/255
 
6.1%
s247
 
6.0%
t247
 
6.0%
o224
 
5.4%
w186
 
4.5%
i169
 
4.1%
m148
 
3.6%
a148
 
3.6%
Other values (30)1847
44.5%

name
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct46
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size536.0 B
Episode 6
 
3
Episode 7
 
2
Episode 8
 
2
Episode 12
 
2
Chanyeol's Episode 21
 
1
Other values (41)
41 

Length

Max length66
Median length41
Mean length18.37254902
Min length5

Characters and Unicode

Total characters937
Distinct characters87
Distinct categories10 ?
Distinct scripts5 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)82.4%

Sample

1st rowChanyeol's Episode 21
2nd row第134集
3rd rowTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~
4th rowForeboding Wind of the Ancient Country
5th rowEpisode 23

Common Values

ValueCountFrequency (%)
Episode 63
 
5.9%
Episode 72
 
3.9%
Episode 82
 
3.9%
Episode 122
 
3.9%
Chanyeol's Episode 211
 
2.0%
Midnight1
 
2.0%
Episode 111
 
2.0%
Taco Night, Any Night1
 
2.0%
A Haunting in West Virginia1
 
2.0%
Selena: The Series1
 
2.0%
Other values (36)36
70.6%

Length

2022-05-09T21:09:47.650330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode17
 
9.6%
the7
 
3.9%
6
 
3.4%
75
 
2.8%
of4
 
2.2%
124
 
2.2%
63
 
1.7%
december3
 
1.7%
prelims2
 
1.1%
program2
 
1.1%
Other values (113)125
70.2%

Most occurring characters

ValueCountFrequency (%)
127
 
13.6%
e74
 
7.9%
o61
 
6.5%
i54
 
5.8%
r48
 
5.1%
a40
 
4.3%
n38
 
4.1%
s37
 
3.9%
d37
 
3.9%
t32
 
3.4%
Other values (77)389
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter585
62.4%
Space Separator127
 
13.6%
Uppercase Letter122
 
13.0%
Decimal Number64
 
6.8%
Other Punctuation17
 
1.8%
Other Letter14
 
1.5%
Dash Punctuation3
 
0.3%
Math Symbol3
 
0.3%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e74
12.6%
o61
10.4%
i54
 
9.2%
r48
 
8.2%
a40
 
6.8%
n38
 
6.5%
s37
 
6.3%
d37
 
6.3%
t32
 
5.5%
l24
 
4.1%
Other values (17)140
23.9%
Uppercase Letter
ValueCountFrequency (%)
E20
16.4%
T10
 
8.2%
F9
 
7.4%
C8
 
6.6%
M8
 
6.6%
P8
 
6.6%
W8
 
6.6%
A7
 
5.7%
S7
 
5.7%
D7
 
5.7%
Other values (13)30
24.6%
Other Letter
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4)4
28.6%
Decimal Number
ValueCountFrequency (%)
117
26.6%
214
21.9%
46
 
9.4%
66
 
9.4%
75
 
7.8%
54
 
6.2%
04
 
6.2%
93
 
4.7%
33
 
4.7%
82
 
3.1%
Other Punctuation
ValueCountFrequency (%)
:4
23.5%
,4
23.5%
.3
17.6%
"2
11.8%
'2
11.8%
?1
 
5.9%
!1
 
5.9%
Math Symbol
ValueCountFrequency (%)
~2
66.7%
|1
33.3%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin702
74.9%
Common216
 
23.1%
Hangul12
 
1.3%
Cyrillic5
 
0.5%
Han2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e74
 
10.5%
o61
 
8.7%
i54
 
7.7%
r48
 
6.8%
a40
 
5.7%
n38
 
5.4%
s37
 
5.3%
d37
 
5.3%
t32
 
4.6%
l24
 
3.4%
Other values (35)257
36.6%
Common
ValueCountFrequency (%)
127
58.8%
117
 
7.9%
214
 
6.5%
46
 
2.8%
66
 
2.8%
75
 
2.3%
:4
 
1.9%
54
 
1.9%
,4
 
1.9%
04
 
1.9%
Other values (13)25
 
11.6%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
Cyrillic
ValueCountFrequency (%)
я1
20.0%
р1
20.0%
е1
20.0%
с1
20.0%
и1
20.0%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII918
98.0%
Hangul12
 
1.3%
Cyrillic5
 
0.5%
CJK2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
 
13.8%
e74
 
8.1%
o61
 
6.6%
i54
 
5.9%
r48
 
5.2%
a40
 
4.4%
n38
 
4.1%
s37
 
4.0%
d37
 
4.0%
t32
 
3.5%
Other values (58)370
40.3%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
Cyrillic
ValueCountFrequency (%)
я1
20.0%
р1
20.0%
е1
20.0%
с1
20.0%
и1
20.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean358.4313725
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:47.947315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36.5
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation776.8135749
Coefficient of variation (CV)2.16725888
Kurtosis1.10133259
Mean358.4313725
Median Absolute Deviation (MAD)0
Skewness1.749176326
Sum18280
Variance603439.3302
MonotonicityNot monotonic
2022-05-09T21:09:48.122315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
128
54.9%
20209
 
17.6%
35
 
9.8%
102
 
3.9%
52
 
3.9%
41
 
2.0%
71
 
2.0%
21
 
2.0%
81
 
2.0%
61
 
2.0%
ValueCountFrequency (%)
128
54.9%
21
 
2.0%
35
 
9.8%
41
 
2.0%
52
 
3.9%
61
 
2.0%
71
 
2.0%
81
 
2.0%
102
 
3.9%
20209
 
17.6%
ValueCountFrequency (%)
20209
 
17.6%
102
 
3.9%
81
 
2.0%
71
 
2.0%
61
 
2.0%
52
 
3.9%
41
 
2.0%
35
 
9.8%
21
 
2.0%
128
54.9%

number
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)52.0%
Missing1
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean19.1
Minimum1
Maximum339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:48.323159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16
median8
Q314.75
95-th percentile49.3
Maximum339
Range338
Interquartile range (IQR)8.75

Descriptive statistics

Standard deviation47.71182628
Coefficient of variation (CV)2.498001376
Kurtosis43.44526775
Mean19.1
Median Absolute Deviation (MAD)4
Skewness6.413864628
Sum955
Variance2276.418367
MonotonicityNot monotonic
2022-05-09T21:09:48.522667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
65
 
9.8%
85
 
9.8%
75
 
9.8%
45
 
9.8%
113
 
5.9%
53
 
5.9%
32
 
3.9%
122
 
3.9%
132
 
3.9%
142
 
3.9%
Other values (16)16
31.4%
ValueCountFrequency (%)
11
 
2.0%
21
 
2.0%
32
 
3.9%
45
9.8%
53
5.9%
65
9.8%
75
9.8%
85
9.8%
91
 
2.0%
113
5.9%
ValueCountFrequency (%)
3391
2.0%
531
2.0%
521
2.0%
461
2.0%
431
2.0%
241
2.0%
231
2.0%
211
2.0%
191
2.0%
181
2.0%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
regular
50 
significant_special
 
1

Length

Max length19
Median length7
Mean length7.235294118
Min length7

Characters and Unicode

Total characters369
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular50
98.0%
significant_special1
 
2.0%

Length

2022-05-09T21:09:48.708006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:48.888705image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular50
98.0%
significant_special1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
r100
27.1%
a52
14.1%
e51
13.8%
g51
13.8%
l51
13.8%
u50
13.6%
i4
 
1.1%
s2
 
0.5%
n2
 
0.5%
c2
 
0.5%
Other values (4)4
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter368
99.7%
Connector Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r100
27.2%
a52
14.1%
e51
13.9%
g51
13.9%
l51
13.9%
u50
13.6%
i4
 
1.1%
s2
 
0.5%
n2
 
0.5%
c2
 
0.5%
Other values (3)3
 
0.8%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin368
99.7%
Common1
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r100
27.2%
a52
14.1%
e51
13.9%
g51
13.9%
l51
13.9%
u50
13.6%
i4
 
1.1%
s2
 
0.5%
n2
 
0.5%
c2
 
0.5%
Other values (3)3
 
0.8%
Common
ValueCountFrequency (%)
_1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r100
27.1%
a52
14.1%
e51
13.8%
g51
13.8%
l51
13.8%
u50
13.6%
i4
 
1.1%
s2
 
0.5%
n2
 
0.5%
c2
 
0.5%
Other values (4)4
 
1.1%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
2020-12-12
51 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters510
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-12
2nd row2020-12-12
3rd row2020-12-12
4th row2020-12-12
5th row2020-12-12

Common Values

ValueCountFrequency (%)
2020-12-1251
100.0%

Length

2022-05-09T21:09:49.037944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:49.192467image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1251
100.0%

Most occurring characters

ValueCountFrequency (%)
2204
40.0%
0102
20.0%
-102
20.0%
1102
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number408
80.0%
Dash Punctuation102
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2204
50.0%
0102
25.0%
1102
25.0%
Dash Punctuation
ValueCountFrequency (%)
-102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2204
40.0%
0102
20.0%
-102
20.0%
1102
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2204
40.0%
0102
20.0%
-102
20.0%
1102
20.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct14
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size536.0 B
nan
30 
20:00
06:00
 
2
12:00
 
2
11:00
 
2
Other values (9)
10 

Length

Max length5
Median length3
Mean length3.823529412
Min length3

Characters and Unicode

Total characters195
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)15.7%

Sample

1st row06:00
2nd row10:00
3rd row12:00
4th row11:00
5th rownan

Common Values

ValueCountFrequency (%)
nan30
58.8%
20:005
 
9.8%
06:002
 
3.9%
12:002
 
3.9%
11:002
 
3.9%
21:002
 
3.9%
10:001
 
2.0%
05:001
 
2.0%
17:001
 
2.0%
18:001
 
2.0%
Other values (4)4
 
7.8%

Length

2022-05-09T21:09:49.319705image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan30
58.8%
20:005
 
9.8%
06:002
 
3.9%
12:002
 
3.9%
11:002
 
3.9%
21:002
 
3.9%
10:001
 
2.0%
05:001
 
2.0%
17:001
 
2.0%
18:001
 
2.0%
Other values (4)4
 
7.8%

Most occurring characters

ValueCountFrequency (%)
n60
30.8%
048
24.6%
a30
15.4%
:21
 
10.8%
115
 
7.7%
211
 
5.6%
54
 
2.1%
63
 
1.5%
71
 
0.5%
81
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter90
46.2%
Decimal Number84
43.1%
Other Punctuation21
 
10.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
048
57.1%
115
 
17.9%
211
 
13.1%
54
 
4.8%
63
 
3.6%
71
 
1.2%
81
 
1.2%
91
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
n60
66.7%
a30
33.3%
Other Punctuation
ValueCountFrequency (%)
:21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common105
53.8%
Latin90
46.2%

Most frequent character per script

Common
ValueCountFrequency (%)
048
45.7%
:21
20.0%
115
 
14.3%
211
 
10.5%
54
 
3.8%
63
 
2.9%
71
 
1.0%
81
 
1.0%
91
 
1.0%
Latin
ValueCountFrequency (%)
n60
66.7%
a30
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n60
30.8%
048
24.6%
a30
15.4%
:21
 
10.8%
115
 
7.7%
211
 
5.6%
54
 
2.1%
63
 
1.5%
71
 
0.5%
81
 
0.5%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size536.0 B
2020-12-12T12:00:00+00:00
21 
2020-12-12T17:00:00+00:00
2020-12-12T04:00:00+00:00
2020-12-12T11:00:00+00:00
2020-12-13T02:00:00+00:00
 
2
Other values (13)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1275
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)23.5%

Sample

1st row2020-12-11T21:00:00+00:00
2nd row2020-12-12T02:00:00+00:00
3rd row2020-12-12T03:00:00+00:00
4th row2020-12-12T03:00:00+00:00
5th row2020-12-12T04:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-12T12:00:00+00:0021
41.2%
2020-12-12T17:00:00+00:006
 
11.8%
2020-12-12T04:00:00+00:005
 
9.8%
2020-12-12T11:00:00+00:003
 
5.9%
2020-12-13T02:00:00+00:002
 
3.9%
2020-12-12T03:00:00+00:002
 
3.9%
2020-12-12T07:00:00+00:001
 
2.0%
2020-12-12T08:00:00+00:001
 
2.0%
2020-12-12T09:00:00+00:001
 
2.0%
2020-12-12T05:00:00+00:001
 
2.0%
Other values (8)8
 
15.7%

Length

2022-05-09T21:09:49.479702image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-12t12:00:00+00:0021
41.2%
2020-12-12t17:00:00+00:006
 
11.8%
2020-12-12t04:00:00+00:005
 
9.8%
2020-12-12t11:00:00+00:003
 
5.9%
2020-12-13t02:00:00+00:002
 
3.9%
2020-12-12t03:00:00+00:002
 
3.9%
2020-12-12t15:15:00+00:001
 
2.0%
2020-12-12t21:15:00+00:001
 
2.0%
2020-12-12t21:00:00+00:001
 
2.0%
2020-12-12t18:50:00+00:001
 
2.0%
Other values (8)8
 
15.7%

Most occurring characters

ValueCountFrequency (%)
0519
40.7%
2228
17.9%
:153
 
12.0%
1145
 
11.4%
-102
 
8.0%
T51
 
4.0%
+51
 
4.0%
77
 
0.5%
45
 
0.4%
35
 
0.4%
Other values (4)9
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number918
72.0%
Other Punctuation153
 
12.0%
Dash Punctuation102
 
8.0%
Uppercase Letter51
 
4.0%
Math Symbol51
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0519
56.5%
2228
24.8%
1145
 
15.8%
77
 
0.8%
45
 
0.5%
35
 
0.5%
55
 
0.5%
82
 
0.2%
91
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:153
100.0%
Dash Punctuation
ValueCountFrequency (%)
-102
100.0%
Uppercase Letter
ValueCountFrequency (%)
T51
100.0%
Math Symbol
ValueCountFrequency (%)
+51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1224
96.0%
Latin51
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0519
42.4%
2228
18.6%
:153
 
12.5%
1145
 
11.8%
-102
 
8.3%
+51
 
4.2%
77
 
0.6%
45
 
0.4%
35
 
0.4%
55
 
0.4%
Other values (3)4
 
0.3%
Latin
ValueCountFrequency (%)
T51
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0519
40.7%
2228
17.9%
:153
 
12.0%
1145
 
11.4%
-102
 
8.0%
T51
 
4.0%
+51
 
4.0%
77
 
0.5%
45
 
0.4%
35
 
0.4%
Other values (4)9
 
0.7%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)52.2%
Missing5
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean43.58695652
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:49.614299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q120.25
median45
Q346.5
95-th percentile113.75
Maximum180
Range175
Interquartile range (IQR)26.25

Descriptive statistics

Standard deviation32.78724419
Coefficient of variation (CV)0.7522260513
Kurtosis6.352395189
Mean43.58695652
Median Absolute Deviation (MAD)15.5
Skewness2.209854599
Sum2005
Variance1075.003382
MonotonicityNot monotonic
2022-05-09T21:09:49.750913image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4512
23.5%
604
 
7.8%
203
 
5.9%
162
 
3.9%
302
 
3.9%
142
 
3.9%
192
 
3.9%
252
 
3.9%
1202
 
3.9%
221
 
2.0%
Other values (14)14
27.5%
(Missing)5
 
9.8%
ValueCountFrequency (%)
51
 
2.0%
121
 
2.0%
142
3.9%
151
 
2.0%
162
3.9%
192
3.9%
203
5.9%
211
 
2.0%
221
 
2.0%
241
 
2.0%
ValueCountFrequency (%)
1801
 
2.0%
1202
 
3.9%
951
 
2.0%
891
 
2.0%
604
 
7.8%
521
 
2.0%
481
 
2.0%
471
 
2.0%
4512
23.5%
441
 
2.0%

image
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct19
Distinct (%)100.0%
Missing32
Missing (%)62.7%
Memory size536.0 B
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/329/823875.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/329/823875.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722381.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722381.jpg'}
 
1
Other values (14)
14 

Length

Max length178
Median length176
Mean length176.2105263
Min length176

Characters and Unicode

Total characters3348
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721377.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721377.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721378.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721378.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/361/903573.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/361/903573.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/394/986669.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/394/986669.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/329/823875.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/329/823875.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722381.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722381.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/404/1010041.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/404/1010041.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/286/716997.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/286/716997.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/329/823868.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/329/823868.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721668.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721668.jpg'}1
 
2.0%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721666.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721666.jpg'}1
 
2.0%
Other values (9)9
 
17.6%
(Missing)32
62.7%

Length

2022-05-09T21:09:49.906929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium19
25.0%
original19
25.0%
https://static.tvmaze.com/uploads/images/medium_landscape/394/986669.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/721364.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/medium_landscape/290/725744.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/original_untouched/290/725744.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726651.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/original_untouched/290/726651.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/medium_landscape/288/720583.jpg1
 
1.3%
https://static.tvmaze.com/uploads/images/original_untouched/288/720583.jpg1
 
1.3%
Other values (30)30
39.5%

Most occurring characters

ValueCountFrequency (%)
/266
 
7.9%
a228
 
6.8%
t209
 
6.2%
m190
 
5.7%
i190
 
5.7%
s171
 
5.1%
e152
 
4.5%
'152
 
4.5%
p133
 
4.0%
o133
 
4.0%
Other values (28)1524
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2242
67.0%
Other Punctuation627
 
18.7%
Decimal Number346
 
10.3%
Space Separator57
 
1.7%
Connector Punctuation38
 
1.1%
Open Punctuation19
 
0.6%
Close Punctuation19
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a228
 
10.2%
t209
 
9.3%
m190
 
8.5%
i190
 
8.5%
s171
 
7.6%
e152
 
6.8%
p133
 
5.9%
o133
 
5.9%
u114
 
5.1%
c114
 
5.1%
Other values (9)608
27.1%
Decimal Number
ValueCountFrequency (%)
266
19.1%
858
16.8%
742
12.1%
638
11.0%
332
9.2%
132
9.2%
024
 
6.9%
922
 
6.4%
420
 
5.8%
512
 
3.5%
Other Punctuation
ValueCountFrequency (%)
/266
42.4%
'152
24.2%
.114
18.2%
:76
 
12.1%
,19
 
3.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Connector Punctuation
ValueCountFrequency (%)
_38
100.0%
Open Punctuation
ValueCountFrequency (%)
{19
100.0%
Close Punctuation
ValueCountFrequency (%)
}19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2242
67.0%
Common1106
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/266
24.1%
'152
13.7%
.114
10.3%
:76
 
6.9%
266
 
6.0%
858
 
5.2%
57
 
5.2%
742
 
3.8%
638
 
3.4%
_38
 
3.4%
Other values (9)199
18.0%
Latin
ValueCountFrequency (%)
a228
 
10.2%
t209
 
9.3%
m190
 
8.5%
i190
 
8.5%
s171
 
7.6%
e152
 
6.8%
p133
 
5.9%
o133
 
5.9%
u114
 
5.1%
c114
 
5.1%
Other values (9)608
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/266
 
7.9%
a228
 
6.8%
t209
 
6.2%
m190
 
5.7%
i190
 
5.7%
s171
 
5.1%
e152
 
4.5%
'152
 
4.5%
p133
 
4.0%
o133
 
4.0%
Other values (28)1524
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size536.0 B
nan
34 
<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>
 
1
<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>
 
1
<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>
 
1
<p>It's game night, so Chef Lovely's making her famous Fried Chicken Sliders with a Creamy Scallion Slaw, Shrimp and Crab Cakes with a Spicy Citrus Remoulade and "Love Cookies" inspired by her Auntie Faye.</p>
 
1
Other values (13)
13 

Length

Max length402
Median length3
Mean length62.90196078
Min length3

Characters and Unicode

Total characters3208
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)33.3%

Sample

1st row<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan34
66.7%
<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>1
 
2.0%
<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>1
 
2.0%
<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>1
 
2.0%
<p>It's game night, so Chef Lovely's making her famous Fried Chicken Sliders with a Creamy Scallion Slaw, Shrimp and Crab Cakes with a Spicy Citrus Remoulade and "Love Cookies" inspired by her Auntie Faye.</p>1
 
2.0%
<p><b>Brennan, Ify, and Ally play a simple, regular game of Jeopardy!</b></p>1
 
2.0%
<p>It's time. </p>1
 
2.0%
<p>The "Dark Eaters" has brought peace to the world by taking out the darkness that feeds on the human heart. One of the only 9 people left in the world with a special ability, Elaiza Ikeda, appears before a "dark-born" Yama, who gives people darkness...</p>1
 
2.0%
<p>Off and Boat have decided to go to an abandoned asylum. As the darkest secret of the asylum reveals, they encounter an accident that has never happened to any show before. </p>1
 
2.0%
<p>It's not Tuesday, but it's tacos! Tregaye Fraser wants to spend more time with her oldest son, so to get a little quality time with Treshawn, Tregaye makes Fish Tacos, Soy Pineapple Flank Steak Tacos, Roast Corn and a Mango Slaw.</p>1
 
2.0%
Other values (8)8
 
15.7%

Length

2022-05-09T21:09:50.086334image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan34
 
6.4%
the31
 
5.8%
to17
 
3.2%
and15
 
2.8%
a12
 
2.2%
with10
 
1.9%
of8
 
1.5%
p7
 
1.3%
in5
 
0.9%
her5
 
0.9%
Other values (320)391
73.1%

Most occurring characters

ValueCountFrequency (%)
480
15.0%
e283
 
8.8%
a245
 
7.6%
n219
 
6.8%
t197
 
6.1%
o155
 
4.8%
i151
 
4.7%
s150
 
4.7%
r148
 
4.6%
h127
 
4.0%
Other values (62)1053
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2368
73.8%
Space Separator487
 
15.2%
Uppercase Letter140
 
4.4%
Other Punctuation106
 
3.3%
Math Symbol88
 
2.7%
Decimal Number15
 
0.5%
Dash Punctuation4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e283
12.0%
a245
10.3%
n219
 
9.2%
t197
 
8.3%
o155
 
6.5%
i151
 
6.4%
s150
 
6.3%
r148
 
6.2%
h127
 
5.4%
l86
 
3.6%
Other values (16)607
25.6%
Uppercase Letter
ValueCountFrequency (%)
T21
15.0%
S15
 
10.7%
A12
 
8.6%
C9
 
6.4%
F8
 
5.7%
Y7
 
5.0%
O7
 
5.0%
P7
 
5.0%
I6
 
4.3%
M5
 
3.6%
Other values (15)43
30.7%
Other Punctuation
ValueCountFrequency (%)
,27
25.5%
.26
24.5%
/23
21.7%
'11
10.4%
"6
 
5.7%
!4
 
3.8%
?3
 
2.8%
#3
 
2.8%
&1
 
0.9%
:1
 
0.9%
Decimal Number
ValueCountFrequency (%)
15
33.3%
04
26.7%
23
20.0%
92
 
13.3%
41
 
6.7%
Space Separator
ValueCountFrequency (%)
480
98.6%
 7
 
1.4%
Math Symbol
ValueCountFrequency (%)
>44
50.0%
<44
50.0%
Dash Punctuation
ValueCountFrequency (%)
-4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2508
78.2%
Common700
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e283
 
11.3%
a245
 
9.8%
n219
 
8.7%
t197
 
7.9%
o155
 
6.2%
i151
 
6.0%
s150
 
6.0%
r148
 
5.9%
h127
 
5.1%
l86
 
3.4%
Other values (41)747
29.8%
Common
ValueCountFrequency (%)
480
68.6%
>44
 
6.3%
<44
 
6.3%
,27
 
3.9%
.26
 
3.7%
/23
 
3.3%
'11
 
1.6%
 7
 
1.0%
"6
 
0.9%
15
 
0.7%
Other values (11)27
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3201
99.8%
None7
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
480
15.0%
e283
 
8.8%
a245
 
7.7%
n219
 
6.8%
t197
 
6.2%
o155
 
4.8%
i151
 
4.7%
s150
 
4.7%
r148
 
4.6%
h127
 
4.0%
Other values (61)1046
32.7%
None
ValueCountFrequency (%)
 7
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct41
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46104.29412
Minimum3734
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:50.274056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum3734
5-th percentile11502
Q147510
median50983
Q352806
95-th percentile59846
Maximum61755
Range58021
Interquartile range (IQR)5296

Descriptive statistics

Standard deviation14319.34607
Coefficient of variation (CV)0.3105859519
Kurtosis2.408132629
Mean46104.29412
Median Absolute Deviation (MAD)2868
Skewness-1.776823996
Sum2351319
Variance205043672
MonotonicityNot monotonic
2022-05-09T21:09:50.421250image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
524514
 
7.8%
511252
 
3.9%
527822
 
3.9%
491472
 
3.9%
252942
 
3.9%
115022
 
3.9%
528062
 
3.9%
479122
 
3.9%
615361
 
2.0%
37341
 
2.0%
Other values (31)31
60.8%
ValueCountFrequency (%)
37341
2.0%
40911
2.0%
115022
3.9%
196671
2.0%
252942
3.9%
306061
2.0%
355511
2.0%
402321
2.0%
408681
2.0%
416481
2.0%
ValueCountFrequency (%)
617551
2.0%
615361
2.0%
608481
2.0%
588441
2.0%
579561
2.0%
579451
2.0%
566051
2.0%
559191
2.0%
558421
2.0%
538881
2.0%

_embedded_show_url
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size536.0 B
https://www.tvmaze.com/shows/52451/the-burning-river
https://www.tvmaze.com/shows/51125/detention
 
2
https://www.tvmaze.com/shows/52782/mr-right-is-here
 
2
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week
 
2
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims
 
2
Other values (36)
39 

Length

Max length64
Median length56
Mean length50.78431373
Min length38

Characters and Unicode

Total characters2590
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)64.7%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/35551/soul-land
3rd rowhttps://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling
4th rowhttps://www.tvmaze.com/shows/51670/heaven-officials-blessing
5th rowhttps://www.tvmaze.com/shows/47912/the-wolf

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52451/the-burning-river4
 
7.8%
https://www.tvmaze.com/shows/51125/detention2
 
3.9%
https://www.tvmaze.com/shows/52782/mr-right-is-here2
 
3.9%
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week2
 
3.9%
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims2
 
3.9%
https://www.tvmaze.com/shows/11502/hver-gang-vi-motes2
 
3.9%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
3.9%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.9%
https://www.tvmaze.com/shows/61536/ano-ko-no-yume-wo-mitan-desu1
 
2.0%
https://www.tvmaze.com/shows/3734/the-streamy-awards1
 
2.0%
Other values (31)31
60.8%

Length

2022-05-09T21:09:50.578123image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52451/the-burning-river4
 
7.8%
https://www.tvmaze.com/shows/52782/mr-right-is-here2
 
3.9%
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week2
 
3.9%
https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelims2
 
3.9%
https://www.tvmaze.com/shows/11502/hver-gang-vi-motes2
 
3.9%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
3.9%
https://www.tvmaze.com/shows/47912/the-wolf2
 
3.9%
https://www.tvmaze.com/shows/51125/detention2
 
3.9%
https://www.tvmaze.com/shows/57956/hjem-til-jul1
 
2.0%
https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling1
 
2.0%
Other values (31)31
60.8%

Most occurring characters

ValueCountFrequency (%)
/255
 
9.8%
w227
 
8.8%
t205
 
7.9%
s199
 
7.7%
o153
 
5.9%
e135
 
5.2%
h132
 
5.1%
m125
 
4.8%
.102
 
3.9%
-96
 
3.7%
Other values (30)961
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1829
70.6%
Other Punctuation408
 
15.8%
Decimal Number257
 
9.9%
Dash Punctuation96
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w227
12.4%
t205
11.2%
s199
10.9%
o153
 
8.4%
e135
 
7.4%
h132
 
7.2%
m125
 
6.8%
a96
 
5.2%
v66
 
3.6%
c66
 
3.6%
Other values (16)425
23.2%
Decimal Number
ValueCountFrequency (%)
554
21.0%
431
12.1%
130
11.7%
229
11.3%
823
8.9%
022
8.6%
920
 
7.8%
618
 
7.0%
716
 
6.2%
314
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/255
62.5%
.102
 
25.0%
:51
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1829
70.6%
Common761
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w227
12.4%
t205
11.2%
s199
10.9%
o153
 
8.4%
e135
 
7.4%
h132
 
7.2%
m125
 
6.8%
a96
 
5.2%
v66
 
3.6%
c66
 
3.6%
Other values (16)425
23.2%
Common
ValueCountFrequency (%)
/255
33.5%
.102
 
13.4%
-96
 
12.6%
554
 
7.1%
:51
 
6.7%
431
 
4.1%
130
 
3.9%
229
 
3.8%
823
 
3.0%
022
 
2.9%
Other values (4)68
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/255
 
9.8%
w227
 
8.8%
t205
 
7.9%
s199
 
7.7%
o153
 
5.9%
e135
 
5.2%
h132
 
5.1%
m125
 
4.8%
.102
 
3.9%
-96
 
3.7%
Other values (30)961
37.1%

_embedded_show_name
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Memory size536.0 B
The Burning River
Detention
 
2
Mr. Right is Here!
 
2
World War Two: Week by Week
 
2
UFC Fight Pass Prelims
 
2
Other values (36)
39 

Length

Max length31
Median length25
Mean length16.05882353
Min length4

Characters and Unicode

Total characters819
Distinct characters65
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)64.7%

Sample

1st rowSim for You
2nd rowSoul Land
3rd rowTokyo Joshi Pro Wrestling
4th rowHeaven Official's Blessing
5th rowThe Wolf

Common Values

ValueCountFrequency (%)
The Burning River4
 
7.8%
Detention2
 
3.9%
Mr. Right is Here!2
 
3.9%
World War Two: Week by Week2
 
3.9%
UFC Fight Pass Prelims2
 
3.9%
Hver gang vi møtes2
 
3.9%
Ultimate Note2
 
3.9%
The Wolf2
 
3.9%
Ano ko no Yume wo Mitan Desu1
 
2.0%
The Streamy Awards1
 
2.0%
Other values (31)31
60.8%

Length

2022-05-09T21:09:50.752487image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the10
 
6.8%
river4
 
2.7%
burning4
 
2.7%
week4
 
2.7%
by3
 
2.0%
prelims2
 
1.4%
to2
 
1.4%
gods2
 
1.4%
lovely2
 
1.4%
no2
 
1.4%
Other values (94)112
76.2%

Most occurring characters

ValueCountFrequency (%)
96
 
11.7%
e80
 
9.8%
i52
 
6.3%
r45
 
5.5%
o43
 
5.3%
a41
 
5.0%
n38
 
4.6%
t36
 
4.4%
s36
 
4.4%
l26
 
3.2%
Other values (55)326
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter572
69.8%
Uppercase Letter135
 
16.5%
Space Separator96
 
11.7%
Other Punctuation12
 
1.5%
Decimal Number4
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e80
14.0%
i52
 
9.1%
r45
 
7.9%
o43
 
7.5%
a41
 
7.2%
n38
 
6.6%
t36
 
6.3%
s36
 
6.3%
l26
 
4.5%
h23
 
4.0%
Other values (24)152
26.6%
Uppercase Letter
ValueCountFrequency (%)
W18
13.3%
T15
 
11.1%
B12
 
8.9%
S10
 
7.4%
R9
 
6.7%
H7
 
5.2%
C7
 
5.2%
P6
 
4.4%
F5
 
3.7%
L5
 
3.7%
Other values (13)41
30.4%
Other Punctuation
ValueCountFrequency (%)
'4
33.3%
:3
25.0%
!2
16.7%
.2
16.7%
?1
 
8.3%
Decimal Number
ValueCountFrequency (%)
22
50.0%
02
50.0%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin700
85.5%
Common112
 
13.7%
Cyrillic7
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e80
 
11.4%
i52
 
7.4%
r45
 
6.4%
o43
 
6.1%
a41
 
5.9%
n38
 
5.4%
t36
 
5.1%
s36
 
5.1%
l26
 
3.7%
h23
 
3.3%
Other values (40)280
40.0%
Common
ValueCountFrequency (%)
96
85.7%
'4
 
3.6%
:3
 
2.7%
22
 
1.8%
02
 
1.8%
!2
 
1.8%
.2
 
1.8%
?1
 
0.9%
Cyrillic
ValueCountFrequency (%)
З1
14.3%
о1
14.3%
м1
14.3%
б1
14.3%
е1
14.3%
т1
14.3%
ы1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII808
98.7%
Cyrillic7
 
0.9%
None4
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
 
11.9%
e80
 
9.9%
i52
 
6.4%
r45
 
5.6%
o43
 
5.3%
a41
 
5.1%
n38
 
4.7%
t36
 
4.5%
s36
 
4.5%
l26
 
3.2%
Other values (46)315
39.0%
None
ValueCountFrequency (%)
ø3
75.0%
å1
 
25.0%
Cyrillic
ValueCountFrequency (%)
З1
14.3%
о1
14.3%
м1
14.3%
б1
14.3%
е1
14.3%
т1
14.3%
ы1
14.3%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
Scripted
22 
Reality
Animation
Sports
Documentary
Other values (4)

Length

Max length11
Median length10
Mean length8.137254902
Min length6

Characters and Unicode

Total characters415
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.9%

Sample

1st rowReality
2nd rowAnimation
3rd rowSports
4th rowAnimation
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted22
43.1%
Reality7
 
13.7%
Animation6
 
11.8%
Sports5
 
9.8%
Documentary4
 
7.8%
Talk Show3
 
5.9%
Game Show2
 
3.9%
Variety1
 
2.0%
Award Show1
 
2.0%

Length

2022-05-09T21:09:51.025843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:51.202766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted22
38.6%
reality7
 
12.3%
animation6
 
10.5%
show6
 
10.5%
sports5
 
8.8%
documentary4
 
7.0%
talk3
 
5.3%
game2
 
3.5%
variety1
 
1.8%
award1
 
1.8%

Most occurring characters

ValueCountFrequency (%)
t45
10.8%
i42
 
10.1%
e36
 
8.7%
S33
 
8.0%
r33
 
8.0%
p27
 
6.5%
c26
 
6.3%
a24
 
5.8%
d23
 
5.5%
o21
 
5.1%
Other values (16)105
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter352
84.8%
Uppercase Letter57
 
13.7%
Space Separator6
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t45
12.8%
i42
11.9%
e36
10.2%
r33
9.4%
p27
7.7%
c26
7.4%
a24
6.8%
d23
 
6.5%
o21
 
6.0%
n16
 
4.5%
Other values (8)59
16.8%
Uppercase Letter
ValueCountFrequency (%)
S33
57.9%
A7
 
12.3%
R7
 
12.3%
D4
 
7.0%
T3
 
5.3%
G2
 
3.5%
V1
 
1.8%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin409
98.6%
Common6
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t45
11.0%
i42
10.3%
e36
 
8.8%
S33
 
8.1%
r33
 
8.1%
p27
 
6.6%
c26
 
6.4%
a24
 
5.9%
d23
 
5.6%
o21
 
5.1%
Other values (15)99
24.2%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t45
10.8%
i42
 
10.1%
e36
 
8.7%
S33
 
8.0%
r33
 
8.0%
p27
 
6.5%
c26
 
6.3%
a24
 
5.8%
d23
 
5.5%
o21
 
5.1%
Other values (16)105
25.3%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
English
18 
Chinese
14 
Norwegian
Korean
Japanese
Other values (4)

Length

Max length9
Median length7
Mean length7.039215686
Min length4

Characters and Unicode

Total characters359
Distinct characters25
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)5.9%

Sample

1st rowKorean
2nd rowChinese
3rd rowJapanese
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English18
35.3%
Chinese14
27.5%
Norwegian7
 
13.7%
Korean3
 
5.9%
Japanese3
 
5.9%
Thai3
 
5.9%
Russian1
 
2.0%
Dutch1
 
2.0%
Arabic1
 
2.0%

Length

2022-05-09T21:09:51.421543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:51.688146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
english18
35.3%
chinese14
27.5%
norwegian7
 
13.7%
korean3
 
5.9%
japanese3
 
5.9%
thai3
 
5.9%
russian1
 
2.0%
dutch1
 
2.0%
arabic1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
n46
12.8%
i44
12.3%
e44
12.3%
s37
10.3%
h36
10.0%
g25
7.0%
a21
 
5.8%
E18
 
5.0%
l18
 
5.0%
C14
 
3.9%
Other values (15)56
15.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter308
85.8%
Uppercase Letter51
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n46
14.9%
i44
14.3%
e44
14.3%
s37
12.0%
h36
11.7%
g25
8.1%
a21
6.8%
l18
 
5.8%
r11
 
3.6%
o10
 
3.2%
Other values (6)16
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
E18
35.3%
C14
27.5%
N7
 
13.7%
K3
 
5.9%
J3
 
5.9%
T3
 
5.9%
R1
 
2.0%
D1
 
2.0%
A1
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin359
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n46
12.8%
i44
12.3%
e44
12.3%
s37
10.3%
h36
10.0%
g25
7.0%
a21
 
5.8%
E18
 
5.0%
l18
 
5.0%
C14
 
3.9%
Other values (15)56
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n46
12.8%
i44
12.3%
e44
12.3%
s37
10.3%
h36
10.0%
g25
7.0%
a21
 
5.8%
E18
 
5.0%
l18
 
5.0%
C14
 
3.9%
Other values (15)56
15.6%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct25
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
[]
14 
['Drama', 'Action', 'Thriller']
['Music']
['Comedy']
['Drama', 'Comedy', 'Adventure']
 
2
Other values (20)
25 

Length

Max length51
Median length40
Mean length18.54901961
Min length2

Characters and Unicode

Total characters946
Distinct characters33
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)29.4%

Sample

1st row[]
2nd row['Action', 'Adventure', 'Anime', 'Fantasy']
3rd row[]
4th row['Drama', 'Anime', 'Fantasy', 'Romance']
5th row['Drama', 'Romance', 'History']

Common Values

ValueCountFrequency (%)
[]14
27.5%
['Drama', 'Action', 'Thriller']4
 
7.8%
['Music']3
 
5.9%
['Comedy']3
 
5.9%
['Drama', 'Comedy', 'Adventure']2
 
3.9%
['Drama', 'Horror', 'Thriller']2
 
3.9%
['Drama', 'Romance']2
 
3.9%
['War', 'History']2
 
3.9%
['Drama', 'Romance', 'History']2
 
3.9%
['Drama', 'Comedy', 'Romance']2
 
3.9%
Other values (15)15
29.4%

Length

2022-05-09T21:09:51.915941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama20
19.4%
14
13.6%
comedy11
10.7%
romance9
8.7%
action7
 
6.8%
thriller6
 
5.8%
adventure5
 
4.9%
anime4
 
3.9%
history4
 
3.9%
horror4
 
3.9%
Other values (10)19
18.4%

Most occurring characters

ValueCountFrequency (%)
'178
18.8%
r60
 
6.3%
a59
 
6.2%
,52
 
5.5%
52
 
5.5%
[51
 
5.4%
]51
 
5.4%
e48
 
5.1%
o46
 
4.9%
m45
 
4.8%
Other values (23)304
32.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter469
49.6%
Other Punctuation230
24.3%
Uppercase Letter91
 
9.6%
Space Separator52
 
5.5%
Open Punctuation51
 
5.4%
Close Punctuation51
 
5.4%
Dash Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r60
12.8%
a59
12.6%
e48
10.2%
o46
9.8%
m45
9.6%
n34
7.2%
i34
7.2%
c26
 
5.5%
t23
 
4.9%
y21
 
4.5%
Other values (7)73
15.6%
Uppercase Letter
ValueCountFrequency (%)
D20
22.0%
A16
17.6%
C13
14.3%
R9
9.9%
H8
 
8.8%
F8
 
8.8%
T7
 
7.7%
M5
 
5.5%
S3
 
3.3%
W2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
'178
77.4%
,52
 
22.6%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
[51
100.0%
Close Punctuation
ValueCountFrequency (%)
]51
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin560
59.2%
Common386
40.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r60
 
10.7%
a59
 
10.5%
e48
 
8.6%
o46
 
8.2%
m45
 
8.0%
n34
 
6.1%
i34
 
6.1%
c26
 
4.6%
t23
 
4.1%
y21
 
3.8%
Other values (17)164
29.3%
Common
ValueCountFrequency (%)
'178
46.1%
,52
 
13.5%
52
 
13.5%
[51
 
13.2%
]51
 
13.2%
-2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'178
18.8%
r60
 
6.3%
a59
 
6.2%
,52
 
5.5%
52
 
5.5%
[51
 
5.4%
]51
 
5.4%
e48
 
5.1%
o46
 
4.9%
m45
 
4.8%
Other values (23)304
32.1%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size536.0 B
Running
32 
Ended
16 
To Be Determined
 
3

Length

Max length16
Median length7
Mean length6.901960784
Min length5

Characters and Unicode

Total characters352
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowEnded

Common Values

ValueCountFrequency (%)
Running32
62.7%
Ended16
31.4%
To Be Determined3
 
5.9%

Length

2022-05-09T21:09:52.093853image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:52.305221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running32
56.1%
ended16
28.1%
to3
 
5.3%
be3
 
5.3%
determined3
 
5.3%

Most occurring characters

ValueCountFrequency (%)
n115
32.7%
i35
 
9.9%
d35
 
9.9%
R32
 
9.1%
u32
 
9.1%
g32
 
9.1%
e28
 
8.0%
E16
 
4.5%
6
 
1.7%
T3
 
0.9%
Other values (6)18
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter289
82.1%
Uppercase Letter57
 
16.2%
Space Separator6
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n115
39.8%
i35
 
12.1%
d35
 
12.1%
u32
 
11.1%
g32
 
11.1%
e28
 
9.7%
o3
 
1.0%
t3
 
1.0%
r3
 
1.0%
m3
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
R32
56.1%
E16
28.1%
T3
 
5.3%
B3
 
5.3%
D3
 
5.3%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin346
98.3%
Common6
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n115
33.2%
i35
 
10.1%
d35
 
10.1%
R32
 
9.2%
u32
 
9.2%
g32
 
9.2%
e28
 
8.1%
E16
 
4.6%
T3
 
0.9%
o3
 
0.9%
Other values (5)15
 
4.3%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n115
32.7%
i35
 
9.9%
d35
 
9.9%
R32
 
9.1%
u32
 
9.1%
g32
 
9.1%
e28
 
8.0%
E16
 
4.5%
6
 
1.7%
T3
 
0.9%
Other values (6)18
 
5.1%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct13
Distinct (%)35.1%
Missing14
Missing (%)27.5%
Infinite0
Infinite (%)0.0%
Mean44.18918919
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:52.447479image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile14
Q120
median45
Q345
95-th percentile120
Maximum180
Range175
Interquartile range (IQR)25

Descriptive statistics

Standard deviation35.84599609
Coefficient of variation (CV)0.8111937952
Kurtosis5.172681986
Mean44.18918919
Median Absolute Deviation (MAD)20
Skewness2.080867943
Sum1635
Variance1284.935435
MonotonicityNot monotonic
2022-05-09T21:09:52.589001image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
4511
21.6%
204
 
7.8%
154
 
7.8%
253
 
5.9%
303
 
5.9%
603
 
5.9%
1202
 
3.9%
902
 
3.9%
161
 
2.0%
101
 
2.0%
Other values (3)3
 
5.9%
(Missing)14
27.5%
ValueCountFrequency (%)
51
 
2.0%
101
 
2.0%
154
 
7.8%
161
 
2.0%
204
 
7.8%
241
 
2.0%
253
 
5.9%
303
 
5.9%
4511
21.6%
603
 
5.9%
ValueCountFrequency (%)
1801
 
2.0%
1202
 
3.9%
902
 
3.9%
603
 
5.9%
4511
21.6%
303
 
5.9%
253
 
5.9%
241
 
2.0%
204
 
7.8%
161
 
2.0%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)58.7%
Missing5
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean43.39130435
Minimum5
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:52.803186image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile10.25
Q120
median44
Q351
95-th percentile117
Maximum180
Range175
Interquartile range (IQR)31

Descriptive statistics

Standard deviation34.51664865
Coefficient of variation (CV)0.7954738666
Kurtosis4.882991847
Mean43.39130435
Median Absolute Deviation (MAD)19.5
Skewness1.959764343
Sum1996
Variance1191.399034
MonotonicityNot monotonic
2022-05-09T21:09:53.063783image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4510
19.6%
253
 
5.9%
152
 
3.9%
542
 
3.9%
202
 
3.9%
742
 
3.9%
302
 
3.9%
512
 
3.9%
172
 
3.9%
1202
 
3.9%
Other values (17)17
33.3%
(Missing)5
 
9.8%
ValueCountFrequency (%)
51
2.0%
91
2.0%
101
2.0%
111
2.0%
131
2.0%
141
2.0%
152
3.9%
161
2.0%
172
3.9%
202
3.9%
ValueCountFrequency (%)
1801
 
2.0%
1202
 
3.9%
1081
 
2.0%
881
 
2.0%
742
 
3.9%
601
 
2.0%
561
 
2.0%
542
 
3.9%
512
 
3.9%
4510
19.6%

_embedded_show_premiered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct36
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
2020-12-11
2020-12-10
2020-12-05
 
3
2012-01-28
 
2
2020-11-07
 
2
Other values (31)
36 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters510
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)51.0%

Sample

1st row2019-03-25
2nd row2018-01-13
3rd row2013-01-30
4th row2020-10-31
5th row2020-11-19

Common Values

ValueCountFrequency (%)
2020-12-114
 
7.8%
2020-12-104
 
7.8%
2020-12-053
 
5.9%
2012-01-282
 
3.9%
2020-11-072
 
3.9%
2018-09-012
 
3.9%
2020-10-032
 
3.9%
2017-01-152
 
3.9%
2020-11-142
 
3.9%
2020-11-192
 
3.9%
Other values (26)26
51.0%

Length

2022-05-09T21:09:53.296592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-114
 
7.8%
2020-12-104
 
7.8%
2020-12-053
 
5.9%
2012-01-282
 
3.9%
2020-11-072
 
3.9%
2018-09-012
 
3.9%
2020-10-032
 
3.9%
2017-01-152
 
3.9%
2020-11-142
 
3.9%
2020-11-192
 
3.9%
Other values (26)26
51.0%

Most occurring characters

ValueCountFrequency (%)
0134
26.3%
2109
21.4%
-102
20.0%
1100
19.6%
918
 
3.5%
312
 
2.4%
710
 
2.0%
89
 
1.8%
47
 
1.4%
56
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number408
80.0%
Dash Punctuation102
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0134
32.8%
2109
26.7%
1100
24.5%
918
 
4.4%
312
 
2.9%
710
 
2.5%
89
 
2.2%
47
 
1.7%
56
 
1.5%
63
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0134
26.3%
2109
21.4%
-102
20.0%
1100
19.6%
918
 
3.5%
312
 
2.4%
710
 
2.0%
89
 
1.8%
47
 
1.4%
56
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0134
26.3%
2109
21.4%
-102
20.0%
1100
19.6%
918
 
3.5%
312
 
2.4%
710
 
2.0%
89
 
1.8%
47
 
1.4%
56
 
1.2%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size536.0 B
nan
35 
2021-01-02
 
3
2020-12-19
 
3
2021-01-04
 
2
2020-12-18
 
2
Other values (4)

Length

Max length10
Median length3
Mean length5.196078431
Min length3

Characters and Unicode

Total characters265
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)3.9%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th row2021-01-04

Common Values

ValueCountFrequency (%)
nan35
68.6%
2021-01-023
 
5.9%
2020-12-193
 
5.9%
2021-01-042
 
3.9%
2020-12-182
 
3.9%
2020-12-262
 
3.9%
2021-01-092
 
3.9%
2020-12-241
 
2.0%
2020-12-121
 
2.0%

Length

2022-05-09T21:09:53.491473image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:53.709139image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan35
68.6%
2021-01-023
 
5.9%
2020-12-193
 
5.9%
2021-01-042
 
3.9%
2020-12-182
 
3.9%
2020-12-262
 
3.9%
2021-01-092
 
3.9%
2020-12-241
 
2.0%
2020-12-121
 
2.0%

Most occurring characters

ValueCountFrequency (%)
n70
26.4%
248
18.1%
039
14.7%
a35
13.2%
-32
12.1%
129
10.9%
95
 
1.9%
43
 
1.1%
82
 
0.8%
62
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number128
48.3%
Lowercase Letter105
39.6%
Dash Punctuation32
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
248
37.5%
039
30.5%
129
22.7%
95
 
3.9%
43
 
2.3%
82
 
1.6%
62
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
n70
66.7%
a35
33.3%
Dash Punctuation
ValueCountFrequency (%)
-32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common160
60.4%
Latin105
39.6%

Most frequent character per script

Common
ValueCountFrequency (%)
248
30.0%
039
24.4%
-32
20.0%
129
18.1%
95
 
3.1%
43
 
1.9%
82
 
1.2%
62
 
1.2%
Latin
ValueCountFrequency (%)
n70
66.7%
a35
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII265
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n70
26.4%
248
18.1%
039
14.7%
a35
13.2%
-32
12.1%
129
10.9%
95
 
1.9%
43
 
1.1%
82
 
0.8%
62
 
0.8%

_embedded_show_officialSite
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct39
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size536.0 B
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d
nan
https://www.netflix.com/title/81329144
 
2
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes
 
2
https://www.youtube.com/c/WorldWarTwo/playlists?view=50&sort=dd&shelf_id=5
 
2
Other values (34)
37 

Length

Max length119
Median length62
Mean length49.78431373
Min length3

Characters and Unicode

Total characters2539
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)60.8%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html
3rd rowhttps://www.ddtpro.com/
4th rowhttps://www.bilibili.com/tgcf
5th rowhttps://www.iqiyi.com/lib/m_213579814.html

Common Values

ValueCountFrequency (%)
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
7.8%
nan4
 
7.8%
https://www.netflix.com/title/813291442
 
3.9%
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes2
 
3.9%
https://www.youtube.com/c/WorldWarTwo/playlists?view=50&sort=dd&shelf_id=52
 
3.9%
https://www.ufc.tv/page/fightpass2
 
3.9%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
3.9%
https://www.iqiyi.com/lib/m_213579814.html2
 
3.9%
https://tv.nrk.no/serie/maskorama1
 
2.0%
https://www.oprah.com/app/lovely-bites.html1
 
2.0%
Other values (29)29
56.9%

Length

2022-05-09T21:09:53.989578image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
7.8%
nan4
 
7.8%
https://www.netflix.com/title/813291442
 
3.9%
https://play.tv2.no/programmer/underholdning/hver-gang-vi-moetes2
 
3.9%
https://www.youtube.com/c/worldwartwo/playlists?view=50&sort=dd&shelf_id=52
 
3.9%
https://www.ufc.tv/page/fightpass2
 
3.9%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
3.9%
https://www.iqiyi.com/lib/m_213579814.html2
 
3.9%
https://www.youtube.com/user/scishow1
 
2.0%
https://independentwrestling.tv/promotion/icw-no-holds-barred1
 
2.0%
Other values (29)29
56.9%

Most occurring characters

ValueCountFrequency (%)
t189
 
7.4%
/187
 
7.4%
s127
 
5.0%
e122
 
4.8%
o119
 
4.7%
.111
 
4.4%
w108
 
4.3%
h100
 
3.9%
a99
 
3.9%
i86
 
3.4%
Other values (60)1291
50.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1733
68.3%
Other Punctuation370
 
14.6%
Decimal Number222
 
8.7%
Uppercase Letter138
 
5.4%
Dash Punctuation30
 
1.2%
Math Symbol27
 
1.1%
Connector Punctuation19
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t189
 
10.9%
s127
 
7.3%
e122
 
7.0%
o119
 
6.9%
w108
 
6.2%
h100
 
5.8%
a99
 
5.7%
i86
 
5.0%
p83
 
4.8%
m78
 
4.5%
Other values (16)622
35.9%
Uppercase Letter
ValueCountFrequency (%)
N16
 
11.6%
P15
 
10.9%
A10
 
7.2%
Y10
 
7.2%
D9
 
6.5%
X8
 
5.8%
C7
 
5.1%
T6
 
4.3%
M6
 
4.3%
W6
 
4.3%
Other values (15)45
32.6%
Decimal Number
ValueCountFrequency (%)
239
17.6%
128
12.6%
626
11.7%
424
10.8%
023
10.4%
920
9.0%
720
9.0%
817
7.7%
314
 
6.3%
511
 
5.0%
Other Punctuation
ValueCountFrequency (%)
/187
50.5%
.111
30.0%
:47
 
12.7%
?10
 
2.7%
&9
 
2.4%
%6
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
-30
100.0%
Math Symbol
ValueCountFrequency (%)
=27
100.0%
Connector Punctuation
ValueCountFrequency (%)
_19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1871
73.7%
Common668
 
26.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t189
 
10.1%
s127
 
6.8%
e122
 
6.5%
o119
 
6.4%
w108
 
5.8%
h100
 
5.3%
a99
 
5.3%
i86
 
4.6%
p83
 
4.4%
m78
 
4.2%
Other values (41)760
40.6%
Common
ValueCountFrequency (%)
/187
28.0%
.111
16.6%
:47
 
7.0%
239
 
5.8%
-30
 
4.5%
128
 
4.2%
=27
 
4.0%
626
 
3.9%
424
 
3.6%
023
 
3.4%
Other values (9)126
18.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t189
 
7.4%
/187
 
7.4%
s127
 
5.0%
e122
 
4.8%
o119
 
4.7%
.111
 
4.4%
w108
 
4.3%
h100
 
3.9%
a99
 
3.9%
i86
 
3.4%
Other values (60)1291
50.8%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct31
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.70588235
Minimum0
Maximum89
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:54.237789image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q117
median25
Q354
95-th percentile81.5
Maximum89
Range89
Interquartile range (IQR)37

Descriptive statistics

Standard deviation24.73402039
Coefficient of variation (CV)0.7126751638
Kurtosis-0.5737041363
Mean34.70588235
Median Absolute Deviation (MAD)15
Skewness0.617244005
Sum1770
Variance611.7717647
MonotonicityNot monotonic
2022-05-09T21:09:54.453916image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
246
 
11.8%
544
 
7.8%
394
 
7.8%
712
 
3.9%
192
 
3.9%
32
 
3.9%
792
 
3.9%
102
 
3.9%
252
 
3.9%
182
 
3.9%
Other values (21)23
45.1%
ValueCountFrequency (%)
01
2.0%
12
3.9%
32
3.9%
61
2.0%
71
2.0%
102
3.9%
131
2.0%
152
3.9%
161
2.0%
182
3.9%
ValueCountFrequency (%)
891
 
2.0%
851
 
2.0%
841
 
2.0%
792
3.9%
712
3.9%
641
 
2.0%
611
 
2.0%
571
 
2.0%
544
7.8%
521
 
2.0%

_embedded_show_dvdCountry
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
nan
51 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters153
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan51
100.0%

Length

2022-05-09T21:09:54.694169image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:09:54.943114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan51
100.0%

Most occurring characters

ValueCountFrequency (%)
n102
66.7%
a51
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter153
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n102
66.7%
a51
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin153
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n102
66.7%
a51
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n102
66.7%
a51
33.3%

_embedded_show_summary
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct40
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size536.0 B
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>
nan
 
2
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>
 
2
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>
 
2
<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>
 
2
Other values (35)
39 

Length

Max length1006
Median length428
Mean length366.3333333
Min length3

Characters and Unicode

Total characters18683
Distinct characters80
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)60.8%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>
3rd rownan
4th row<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>
5th row<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>

Common Values

ValueCountFrequency (%)
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
7.8%
nan2
 
3.9%
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
3.9%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>2
 
3.9%
<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>2
 
3.9%
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>2
 
3.9%
<p>7 artists spend eight days together at a farm outside the city of Moss, where each artist attempts to do their own version of another artists well-known songs, with each person getting an episode featuring all of their songs being performed by the other musicians.</p>2
 
3.9%
<p>World War Two dives into the history of one of the most devastating wars in human history. Indy Neidell, Spartacus Olsson and their team of dedicated historians cover the events of World War Two week by week in realtime. Additionally, we take an in-depth look at the war against humanity, key figures in all camps, military hardware, impact on culture, military strategies and life at the home fronts or under occupation.</p>2
 
3.9%
<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>2
 
3.9%
<p>On <b>WWE Talking Smack</b>, Renee Young catches up with your favorite SmackDown Superstars after "Smackdown Live" airs on the USA Network to hear their thoughts on all of that evening's action.</p>1
 
2.0%
Other values (30)30
58.8%

Length

2022-05-09T21:09:55.163953image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the202
 
6.5%
and123
 
4.0%
a101
 
3.2%
to80
 
2.6%
of79
 
2.5%
in62
 
2.0%
is33
 
1.1%
with29
 
0.9%
he29
 
0.9%
by26
 
0.8%
Other values (1092)2347
75.4%

Most occurring characters

ValueCountFrequency (%)
3049
16.3%
e1736
 
9.3%
t1232
 
6.6%
a1187
 
6.4%
n1090
 
5.8%
o1075
 
5.8%
i1037
 
5.6%
s969
 
5.2%
r815
 
4.4%
h778
 
4.2%
Other values (70)5715
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14144
75.7%
Space Separator3066
 
16.4%
Uppercase Letter542
 
2.9%
Other Punctuation503
 
2.7%
Math Symbol336
 
1.8%
Dash Punctuation38
 
0.2%
Decimal Number31
 
0.2%
Format12
 
0.1%
Open Punctuation5
 
< 0.1%
Close Punctuation5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1736
12.3%
t1232
 
8.7%
a1187
 
8.4%
n1090
 
7.7%
o1075
 
7.6%
i1037
 
7.3%
s969
 
6.9%
r815
 
5.8%
h778
 
5.5%
d537
 
3.8%
Other values (17)3688
26.1%
Uppercase Letter
ValueCountFrequency (%)
T65
 
12.0%
S45
 
8.3%
A35
 
6.5%
W34
 
6.3%
C31
 
5.7%
H29
 
5.4%
L29
 
5.4%
I27
 
5.0%
F26
 
4.8%
O24
 
4.4%
Other values (16)197
36.3%
Other Punctuation
ValueCountFrequency (%)
,188
37.4%
.148
29.4%
/86
17.1%
'33
 
6.6%
"24
 
4.8%
!13
 
2.6%
?5
 
1.0%
:3
 
0.6%
;2
 
0.4%
&1
 
0.2%
Decimal Number
ValueCountFrequency (%)
011
35.5%
95
16.1%
15
16.1%
25
16.1%
72
 
6.5%
32
 
6.5%
41
 
3.2%
Space Separator
ValueCountFrequency (%)
3049
99.4%
 17
 
0.6%
Math Symbol
ValueCountFrequency (%)
>168
50.0%
<168
50.0%
Dash Punctuation
ValueCountFrequency (%)
-31
81.6%
7
 
18.4%
Format
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
(5
100.0%
Close Punctuation
ValueCountFrequency (%)
)5
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14686
78.6%
Common3997
 
21.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1736
11.8%
t1232
 
8.4%
a1187
 
8.1%
n1090
 
7.4%
o1075
 
7.3%
i1037
 
7.1%
s969
 
6.6%
r815
 
5.5%
h778
 
5.3%
d537
 
3.7%
Other values (43)4230
28.8%
Common
ValueCountFrequency (%)
3049
76.3%
,188
 
4.7%
>168
 
4.2%
<168
 
4.2%
.148
 
3.7%
/86
 
2.2%
'33
 
0.8%
-31
 
0.8%
"24
 
0.6%
 17
 
0.4%
Other values (17)85
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII18645
99.8%
Punctuation20
 
0.1%
None18
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3049
16.4%
e1736
 
9.3%
t1232
 
6.6%
a1187
 
6.4%
n1090
 
5.8%
o1075
 
5.8%
i1037
 
5.6%
s969
 
5.2%
r815
 
4.4%
h778
 
4.2%
Other values (65)5677
30.4%
None
ValueCountFrequency (%)
 17
94.4%
æ1
 
5.6%
Punctuation
ValueCountFrequency (%)
12
60.0%
7
35.0%
1
 
5.0%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION

Distinct41
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1635030204
Minimum1607798027
Maximum1652080636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size536.0 B
2022-05-09T21:09:55.592668image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1607798027
5-th percentile1608033303
Q11619532484
median1643317205
Q31648283134
95-th percentile1651896878
Maximum1652080636
Range44282609
Interquartile range (IQR)28750651

Descriptive statistics

Standard deviation16576846.21
Coefficient of variation (CV)0.01013855657
Kurtosis-1.181114737
Mean1635030204
Median Absolute Deviation (MAD)6955121
Skewness-0.7091454198
Sum8.338654038 × 1010
Variance2.747918302 × 1014
MonotonicityNot monotonic
2022-05-09T21:09:55.842479image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
16080333034
 
7.8%
16098872012
 
3.9%
16096716402
 
3.9%
16520806362
 
3.9%
16465289862
 
3.9%
16455195302
 
3.9%
16491780842
 
3.9%
16482170292
 
3.9%
16497926551
 
2.0%
16152354381
 
2.0%
Other values (31)31
60.8%
ValueCountFrequency (%)
16077980271
 
2.0%
16080333034
7.8%
16084990071
 
2.0%
16093598271
 
2.0%
16096716402
3.9%
16098872012
3.9%
16114368421
 
2.0%
16152354381
 
2.0%
16238295291
 
2.0%
16238296751
 
2.0%
ValueCountFrequency (%)
16520806362
3.9%
16520294141
2.0%
16517643421
2.0%
16516375911
2.0%
16509088001
2.0%
16507118491
2.0%
16500169181
2.0%
16497926551
2.0%
16491780842
3.9%
16486966511
2.0%

_links_self_href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size536.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2006091
 
1
https://api.tvmaze.com/episodes/2090654
 
1
https://api.tvmaze.com/episodes/2090655
 
1
https://api.tvmaze.com/episodes/2169203
 
1
Other values (46)
46 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters1989
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
2.0%
https://api.tvmaze.com/episodes/20060911
 
2.0%
https://api.tvmaze.com/episodes/20906541
 
2.0%
https://api.tvmaze.com/episodes/20906551
 
2.0%
https://api.tvmaze.com/episodes/21692031
 
2.0%
https://api.tvmaze.com/episodes/23122231
 
2.0%
https://api.tvmaze.com/episodes/23122241
 
2.0%
https://api.tvmaze.com/episodes/23122251
 
2.0%
https://api.tvmaze.com/episodes/23122261
 
2.0%
https://api.tvmaze.com/episodes/23122271
 
2.0%
Other values (41)41
80.4%

Length

2022-05-09T21:09:56.391212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
2.0%
https://api.tvmaze.com/episodes/23244331
 
2.0%
https://api.tvmaze.com/episodes/19640001
 
2.0%
https://api.tvmaze.com/episodes/19954051
 
2.0%
https://api.tvmaze.com/episodes/20077601
 
2.0%
https://api.tvmaze.com/episodes/19857891
 
2.0%
https://api.tvmaze.com/episodes/20396221
 
2.0%
https://api.tvmaze.com/episodes/20396231
 
2.0%
https://api.tvmaze.com/episodes/23244271
 
2.0%
https://api.tvmaze.com/episodes/23244281
 
2.0%
Other values (41)41
80.4%

Most occurring characters

ValueCountFrequency (%)
/204
 
10.3%
t153
 
7.7%
p153
 
7.7%
s153
 
7.7%
e153
 
7.7%
a102
 
5.1%
i102
 
5.1%
.102
 
5.1%
m102
 
5.1%
o102
 
5.1%
Other values (16)663
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1275
64.1%
Other Punctuation357
 
17.9%
Decimal Number357
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t153
12.0%
p153
12.0%
s153
12.0%
e153
12.0%
a102
8.0%
i102
8.0%
m102
8.0%
o102
8.0%
h51
 
4.0%
d51
 
4.0%
Other values (3)153
12.0%
Decimal Number
ValueCountFrequency (%)
278
21.8%
947
13.2%
142
11.8%
041
11.5%
330
 
8.4%
426
 
7.3%
826
 
7.3%
723
 
6.4%
523
 
6.4%
621
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/204
57.1%
.102
28.6%
:51
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1275
64.1%
Common714
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/204
28.6%
.102
14.3%
278
 
10.9%
:51
 
7.1%
947
 
6.6%
142
 
5.9%
041
 
5.7%
330
 
4.2%
426
 
3.6%
826
 
3.6%
Other values (3)67
 
9.4%
Latin
ValueCountFrequency (%)
t153
12.0%
p153
12.0%
s153
12.0%
e153
12.0%
a102
8.0%
i102
8.0%
m102
8.0%
o102
8.0%
h51
 
4.0%
d51
 
4.0%
Other values (3)153
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1989
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/204
 
10.3%
t153
 
7.7%
p153
 
7.7%
s153
 
7.7%
e153
 
7.7%
a102
 
5.1%
i102
 
5.1%
.102
 
5.1%
m102
 
5.1%
o102
 
5.1%
Other values (16)663
33.3%

Interactions

2022-05-09T21:09:41.152367image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:15.905406image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:20.723653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:23.945830image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:26.945240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:28.723859image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:32.493906image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:35.068051image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:37.405154image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:42.010830image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:17.196960image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:21.951812image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:25.310000image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:27.280547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:29.675179image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:32.998308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:35.541674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:38.648863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:42.218078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:17.834378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:22.211431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:25.521982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:27.431576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:29.927848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:33.282281image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:35.774143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:38.871667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:42.373425image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:18.311030image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:22.490705image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:25.740082image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:27.568030image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:30.222243image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:33.511182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:36.059412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:39.238221image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:42.618472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:18.640806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:22.673813image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:25.914450image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:27.712518image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:30.496904image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:33.707545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:36.264840image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:39.715502image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:43.018358image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:19.198443image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:23.059527image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:26.273409image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:27.987995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:30.912675image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:34.215307image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:36.642287image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:40.240036image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:43.238394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:19.447381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:23.248688image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:26.430363image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:28.145167image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:31.158934image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:34.423275image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:36.837296image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:40.448338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:43.413184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:19.719520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:23.604561image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:26.606610image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:28.293169image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:31.559555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:34.614964image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:37.041288image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:40.822742image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:43.580941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:20.179018image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:23.772124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:26.770407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:28.415749image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:32.051338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:34.862814image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:37.215714image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:09:40.992496image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:09:56.622278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:09:56.943653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:09:57.204487image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:09:57.505392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:09:58.004889image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:09:43.935289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:09:45.423126image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:09:45.823615image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:09:46.055070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01988859https://www.tvmaze.com/episodes/1988859/sim-for-you-4x21-chanyeols-episode-21Chanyeol's Episode 214.021.0regular2020-12-1206:002020-12-11T21:00:00+00:0016.0None<p><b>#LastNightOfSummerVacation #10PointsOutof10 #TheRevealoftheFinalGift</b></p>41648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25nanhttps://www.vlive.tv/video/12163771.0nan<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1.608499e+09https://api.tvmaze.com/episodes/1977902
11986140https://www.tvmaze.com/episodes/1986140/soul-land-7x04-di134ji第134集7.04.0regular2020-12-1210:002020-12-12T02:00:00+00:0020.0Nonenan35551https://www.tvmaze.com/shows/35551/soul-landSoul LandAnimationChinese['Action', 'Adventure', 'Anime', 'Fantasy']Running20.020.02018-01-13nanhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html89.0nan<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>1.643317e+09https://api.tvmaze.com/episodes/2015818
22138925https://www.tvmaze.com/episodes/2138925/tokyo-joshi-pro-wrestling-2020-12-12-tjpw-fall-tour-20-womm-wrestling-of-my-mindTJPW Fall Tour '20 ~ WOMM (Wrestling Of My Mind) ~2020.043.0regular2020-12-1212:002020-12-12T03:00:00+00:00120.0Nonenan49740https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestlingTokyo Joshi Pro WrestlingSportsJapanese[]Running120.0120.02013-01-30nanhttps://www.ddtpro.com/13.0nannan1.651764e+09https://api.tvmaze.com/episodes/1964000
31962057https://www.tvmaze.com/episodes/1962057/heaven-officials-blessing-1x08-foreboding-wind-of-the-ancient-countryForeboding Wind of the Ancient Country1.08.0regular2020-12-1211:002020-12-12T03:00:00+00:0025.0Nonenan51670https://www.tvmaze.com/shows/51670/heaven-officials-blessingHeaven Official's BlessingAnimationChinese['Drama', 'Anime', 'Fantasy', 'Romance']Running25.025.02020-10-31nanhttps://www.bilibili.com/tgcf52.0nan<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>1.637712e+09https://api.tvmaze.com/episodes/1995405
41972565https://www.tvmaze.com/episodes/1972565/the-wolf-1x23-episode-23Episode 231.023.0regular2020-12-12nan2020-12-12T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/2007760
51972566https://www.tvmaze.com/episodes/1972566/the-wolf-1x24-episode-24Episode 241.024.0regular2020-12-12nan2020-12-12T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/1985789
61998578https://www.tvmaze.com/episodes/1998578/mr-right-is-here-1x07-episode-7Episode 71.07.0regular2020-12-12nan2020-12-12T04:00:00+00:0045.0Nonenan52782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese['Drama', 'Comedy', 'Romance']Ended45.045.02020-12-102020-12-18nan15.0nan<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1.609672e+09https://api.tvmaze.com/episodes/2039622
71998579https://www.tvmaze.com/episodes/1998579/mr-right-is-here-1x08-episode-8Episode 81.08.0regular2020-12-12nan2020-12-12T04:00:00+00:0045.0Nonenan52782https://www.tvmaze.com/shows/52782/mr-right-is-hereMr. Right is Here!ScriptedChinese['Drama', 'Comedy', 'Romance']Ended45.045.02020-12-102020-12-18nan15.0nan<p>‎The fashion company faced a crisis. Sun Chi, the young owner of the company, at a critical moment took over the management and became the new CEO. He promised his father that in three months he would be able to promote the project "promoting fashion" that will help to get out of the crisis. ‎ </p><p>‎Gio Intao, who wanted to be the queen of the fashion industry, by coincidence got into the company and became subordinate to the "devil", a young gene. Director Sun Chi.‎   </p><p>‎Sun Chi and Xiao Intao led a fashion company to resolve the crisis and open new markets, allowing Chinese fashion brands to enter the global market step by step. At the same time, they begin to feel each other.‎</p>1.609672e+09https://api.tvmaze.com/episodes/2039623
82113320https://www.tvmaze.com/episodes/2113320/klassen-3x18-herman-dahl-tar-overHerman Dahl tar over3.018.0regular2020-12-1205:002020-12-12T04:00:00+00:0012.0Nonenan55919https://www.tvmaze.com/shows/55919/klassenKlassenScriptedNorwegian['Drama', 'Comedy', 'Children']RunningNaN10.02019-09-06nanhttps://tv.nrk.no/serie/klassen57.0nan<p>Livet i klassen er som en berg- og dalbane av kjærlighet, vennskap og samhold.</p>1.650712e+09https://api.tvmaze.com/episodes/2324427
91977320https://www.tvmaze.com/episodes/1977320/stjernestov-1x12-episode-12Episode 121.012.0regular2020-12-1206:002020-12-12T05:00:00+00:0020.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726346.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726346.jpg'}nan50752https://www.tvmaze.com/shows/50752/stjernestovStjernestøvScriptedNorwegian['Drama', 'Children', 'Family']Ended20.020.02020-12-012020-12-24https://tv.nrk.no/serie/stjernestoev22.0nan<p>The parents get divorced and Jo has to move to a new place. One day, Nordstjerna goes out, and Jo discovers that a girl with magical powers lives in the attic.</p>1.611437e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
412042787https://www.tvmaze.com/episodes/2042787/ufc-fight-pass-prelims-2020-12-12-ufc-256-figueiredo-vs-moreno-early-prelimsUFC 256: Figueiredo vs. Moreno Early Prelims2020.052.0regular2020-12-12nan2020-12-12T17:00:00+00:0060.0Nonenan25294https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelimsUFC Fight Pass PrelimsSportsEnglish[]Running60.074.02017-01-15nanhttps://www.ufc.tv/page/fightpass39.0nan<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>1.646529e+09https://api.tvmaze.com/episodes/2015837
422042788https://www.tvmaze.com/episodes/2042788/ufc-fight-pass-prelims-2020-12-12-ufc-256-figueiredo-vs-moreno-prelimsUFC 256: Figueiredo vs. Moreno Prelims2020.053.0regular2020-12-12nan2020-12-12T17:00:00+00:0060.0Nonenan25294https://www.tvmaze.com/shows/25294/ufc-fight-pass-prelimsUFC Fight Pass PrelimsSportsEnglish[]Running60.074.02017-01-15nanhttps://www.ufc.tv/page/fightpass39.0nan<p>Televised undercard bouts from UFC Pay-Per-Views and UFC Fight Nights exclusively on UFC Fight Pass.</p>1.646529e+09https://api.tvmaze.com/episodes/1996819
432071506https://www.tvmaze.com/episodes/2071506/game-changer-3x07-jeopardyJeopardy!3.07.0regular2020-12-1212:002020-12-12T17:00:00+00:0034.0None<p><b>Brennan, Ify, and Ally play a simple, regular game of Jeopardy!</b></p>50895https://www.tvmaze.com/shows/50895/game-changerGame ChangerGame ShowEnglish['Comedy']Running25.025.02019-09-20nanhttps://www.youtube.com/channel/UCPDXXXJj9nax0fr0Wfc048g85.0nan<p>In this game show, the game changes every show! Players begin each round without knowing the rules -- and must figure them out while competing to win.</p>1.648349e+09https://api.tvmaze.com/episodes/2037724
441943280https://www.tvmaze.com/episodes/1943280/rail-romanesque-1x11-the-soothing-hot-springsThe Soothing Hot Springs1.011.0regular2020-12-12nan2020-12-12T17:00:00+00:005.0Nonenan50939https://www.tvmaze.com/shows/50939/rail-romanesqueRail RomanesqueAnimationJapanese['Comedy', 'Anime', 'Science-Fiction']Ended5.05.02020-10-032020-12-19https://railromanesque.jp24.0nan<p>Set in Hinomoto, a fictional version of Japan, where for a long time railway travel served as the most important form of transport. Each locomotive was paired with a humanoid control module, so-called Raillord, that aided the train operator. However, many rail lines had been discontinued due to the rising popularity of "aerocrafts," a safe and convenient aerial mode of transport. As such, their accompanying railroads also went into a deep sleep. Soutetsu had lost his entire family in a rail accident and was adopted into the Migita household, which runs a shochu brewery in the city of Ohitoyo. He returned to his hometown to save it from the potential water pollution that would occur if they accepted the proposal to build an aerocraft factory nearby. He woke up the Raillord Hachiroku by accident and became her owner. For different purposes, they agreed to help find her lost locomotive, with the help of his stepsister Hibiki, the town's mayor and local railway chief, Paulette and others.</p>1.645753e+09https://api.tvmaze.com/episodes/2037725
452037519https://www.tvmaze.com/episodes/2037519/lovely-bites-by-chef-lovely-1x05-get-your-game-onGet Your Game On1.05.0regular2020-12-12nan2020-12-12T17:00:00+00:0025.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/329/823875.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/329/823875.jpg'}<p>It's game night, so Chef Lovely's making her famous Fried Chicken Sliders with a Creamy Scallion Slaw, Shrimp and Crab Cakes with a Spicy Citrus Remoulade and "Love Cookies" inspired by her Auntie Faye.</p>53754https://www.tvmaze.com/shows/53754/lovely-bites-by-chef-lovelyLovely Bites by Chef LovelyRealityEnglish[]Running25.025.02020-11-14nanhttps://www.oprah.com/app/lovely-bites.html19.0nan<p>Chef Connie "Lovely" Jackson brings the fun with recipes that are perfect for entertaining and celebrating festive occasions. <b>Lovely Bites</b> is produced for OWN by FishBowl Worldwide Media.</p>1.623830e+09https://api.tvmaze.com/episodes/1988424
461967068https://www.tvmaze.com/episodes/1967068/maskorama-1x06-episode-6Episode 61.06.0regular2020-12-1219:502020-12-12T18:50:00+00:0089.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/722361.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/722361.jpg'}<p>Finale! The last three participants will go through the finals and gold finals. Tonight we are left with one winner and three revelations! Did you guess correctly?</p>51314https://www.tvmaze.com/shows/51314/maskoramaMaskoramaRealityNorwegian['Music']Running90.088.02020-11-07nanhttps://tv.nrk.no/serie/maskorama18.0nan<p>Based on the international hit "The Masked Singer", in <b>Maskorama </b>eight elebrities will face off against one another with a twist: each singer is using masks and costumes, the judges panel will have to guess which celebrity is behind the mask.</p>1.640455e+09https://api.tvmaze.com/episodes/1993940
471982435https://www.tvmaze.com/episodes/1982435/onyx-equinox-1x04-the-strangerThe Stranger1.04.0regular2020-12-1216:002020-12-12T21:00:00+00:0024.0None<p>lzel, K'in and Yun head towards the second gate at Lakamha, where they encounter a warrior looking to bargain.</p>48922https://www.tvmaze.com/shows/48922/onyx-equinoxOnyx EquinoxAnimationEnglish['Action', 'Adventure', 'Fantasy']Ended24.024.02020-11-212020-12-26https://www.crunchyroll.com/onyx-equinox46.0nan<p>A young Aztec boy is saved from death by the gods and chosen to act as ‘humanity's champion,' forced to discard his apathy toward his fellow man and prove humanity's potential in a fight that spans across fantastical-yet-authentic Mesoamerican cultures.</p>1.609360e+09https://api.tvmaze.com/episodes/2037532
481972346https://www.tvmaze.com/episodes/1972346/eides-spraksjov-6x04-trompetvokabularetTrompetvokabularet6.04.0regular2020-12-1222:152020-12-12T21:15:00+00:0045.0Nonenan51631https://www.tvmaze.com/shows/51631/eides-spraksjovEides språksjovTalk ShowNorwegian['Comedy']RunningNaN43.02017-01-11nanhttps://tv.nrk.no/serie/eides-spraaksjov3.0nan<p>Entertainment from here to the moon when Linda Eide and guests pay tribute and joke with language.</p>1.650017e+09https://api.tvmaze.com/episodes/2068252
491982904https://www.tvmaze.com/episodes/1982904/the-streamy-awards-2020-12-12-the-10th-annual-streamy-awardsThe 10th Annual Streamy Awards2020.01.0regular2020-12-1221:002020-12-13T02:00:00+00:0095.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/288/721362.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/288/721362.jpg'}<p>Join hosts Trixie and Katya for the 2020 YouTube Streamy Awards as we honor the best of our creator community. Watch it free December 12 with ads on YouTube or sign up for YouTube Premium to watch exclusive Q&amp;As with Streamys creators that you won't find anywhere else.</p>3734https://www.tvmaze.com/shows/3734/the-streamy-awardsThe Streamy AwardsAward ShowEnglish[]Running90.0108.02009-03-28nanhttp://www.streamys.org37.0nan<p><b>The Streamy Awards </b>honor the best in online video and the creators behind it. The annual event brings together the biggest names in YouTube and online video for a night of celebration, discovery, and meaningful recognition.</p>1.615235e+09https://api.tvmaze.com/episodes/1996820
502042203https://www.tvmaze.com/episodes/2042203/cage-warriors-2020-12-12-cage-warriors-119Cage Warriors 1192020.08.0regular2020-12-1221:002020-12-13T02:00:00+00:00120.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/402/1005471.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/402/1005471.jpg'}nan50594https://www.tvmaze.com/shows/50594/cage-warriorsCage WarriorsSportsEnglish[]Running120.0120.02002-07-27nanhttps://cagewarriors.com16.0nan<p><b>Cage Warriors</b> is a mixed martial arts promotion, based in London. The promotion was established in 2001 and staged its first MMA event in London in July, 2002. </p>1.648697e+09https://api.tvmaze.com/episodes/1985251